Her Globalink research internship project under Professor Dae-Sik Moon at the University of Toronto’s Department of Astronomy and Astrophysics is employing new technology that was originally developed for the James Webb Space Telescope — a collaboration between NASA, the European Space Agency and the Canadian Space Agency. Aishwarya’s project involves selecting and testing optical components that will ultimately give astronomers the ability to see the faintest glows of light from the earliest moments of the universe, as well as the formation of stars, planetary systems and galaxies.
An abundance of choice presents users of many online and mobile platforms. Sorting through this to find desirable content is a challenge for users. To assist with this challenge and increase user interaction it is common to implement a recommendation system that can predict what kind of content a user will or will not be interested in. Wattpad uses such a recommendation system to connect users with stories. The research project will seek to identify relevant factors which can be used to improve the quality of recommendations given thereby building a stronger reader community.
The effective planning of resources when scheduling maintenance tasks and repair jobs is an enormous challenge, especially for heavy industries such as aerospace and transportation manufacturers. In such industries, because of the product complexity and variety, not to mention continuous technological improvements, a broad range of maintenance tasks and high-performance services should be done over the course of a year to guarantee the safety and reliability of the products.
As the game of basketball evolved, analysis of the game has also grown from taking average of field goal percentage to more complex analytics. In the 2013-2014 season, the NBA has installed the SportVU Player Tracking technology in every NBA arena. SportVU collects 25 frames of data per second, each frame containing the (x,y) coordinates of each of the 10 players and the (x,y,z) coordinates of the basketball.
Facing looming infrastructure crises, municipalities around the world are implementing asset management policies to maximize level of service to residents through optimized scheduling of maintenance, rehabilitation, and replacement of assets. Scheduling optimization problems have been studied extensively in computer science and it is believed that an exact solution to such a problem would take an impractical amount of time to compute. However, several methods for finding approximate solutions have been proposed.
The project is focused on study of commercial microbial cultures for biological remediation of soils and ground waters contaminated by chlorinated organic. The successful elaboration and improvement of the products requires analysis on molecular-genetic level and developing of specific techniques (16S pyrotag pipeline) for microbial communities profiling and metabolic reconstruction. The work benefits to industry partner by providing comprehensive information on functional and taxonomic structure of the studied microbial communities.
Mobile robots equipped with chemical, radiological and explosive detectors are deployed during events where CBRNE materials have been dispersed; sending robots provides key reconnaissance data while reducing personnel exposure. Operators rely on camera views and on-board detectors to drive the robots using joysticks, and they have to control every aspect of the robot operation. Live detector data collected by the robot can be overlaid on maps.
The project will develop a data mining strategy on how to efficiently use Geotab’s data from multiple sources to isolate network connectivity logs in Geotab’s data, interpolate the GPS coordinates associated with network logs, acquire fuel consumption rates and related opportunities. It will involve a literature survey of the existing algorithms to gain valuable insights. It will also include an important research component to analyze, understand, and develop trends using the available data to compare and corelate the results.
Perform an exploratory research to investigate the potential to extract knowledge by aggregating historical data across the company's clients and applying machine learning techniques on them. The goal is to device prediction models that can forecast the condition of certain events(such as life of pipelines) using statistical analysis. Riva Modeling( partner organization) will benefit from the results of the research by being able to draw more meaningful inferences from the large amount of historical data available from the clients.
Through this research project the intern will investigate the potential of data visualization incorporating a social collaboration element tied to typical data types in asset management. The partner organization Riva Modeling Systems will benefit from the proposed research by providing its clients with an enhanced asset management tool that allows various groups or individuals within the client organization to collaborate in various data views and to see their interaction records on the central dashboard with visualized data.